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src/n/i/nipy-0.3.0/nipy/labs/spatial_models/bayesian_structural_analysis.py   nipy(Download)
    migmm._prior_scale = np.diag(prior_precision[0] / dof)
    migmm._inv_prior_scale_ = [np.diag(dof * 1. / (prior_precision[0]))]
    migmm.sample(gfc, null_class_proba=1 - gf1, niter=burnin, init=False,
                 kfold=sub)
    if verbose:
    if co_clust:
        like, pproba, co_clust = migmm.sample(
            gfc, null_class_proba=1 - gf1, niter=nis,
            sampling_points=spatial_coords, kfold=sub, co_clustering=co_clust)
        if verbose:
    else:
        like, pproba = migmm.sample(
            gfc, null_class_proba=1 - gf1, niter=nis,
            sampling_points=spatial_coords, kfold=sub, co_clustering=co_clust)
    if verbose: